Globally over 3 billion people rely on biomass as their million deaths annually, more than the number of deaths from malaria and tuberculosis. This Mentored Research Scientist Development Award is focused on developing an integrated research program that addresses the determinants of fuel and technology use and their associated health and socioeconomic outcomes in sub-Saharan Africa (SSA). While the household-level determinants of fuel use and cooking technologies are relatively well understood, few studies model a comprehensive set of both supply and demand side determinants of fuel and technology use. The project tests the central hypothesis that meso and macro level variables including land use and land cover change, population dynamics, and variable rates of infrastructure and market development influence fuel and technology options, and in turn observed respiratory health, nutrition, and socioeconomic outcomes. Specific aims include: (1) developing and testing a multi-level spatial model of the determinants of fuel and technology use in Malawi; (2) developing and testing a comprehensive and appropriate set of measures and field methods for understanding respiratory and nutritional outcomes associated with fuel and technology use; and (3) estimating a dynamic multi-level spatial model that integrates the determinants of fuel and technology use with health and socioeconomic outcomes. To achieve the objectives and test hypotheses, the study proposes to combine theory and methods from the fields of epidemiology, nutrition, environmental health, political economy, demography, welfare and development economics, and uses cutting edge methods including spatial epidemiology and dynamic multi-level modeling. The findings from this study will have a wide impact on targeting of public programs aimed at reducing the negative health impacts of exposure to biomass smoke, specifically, acute respiratory infection, chronic respiratory illness, low birth weight, and under nutrition throughout SSA. The training component of this award will enable me to: (a) obtain training in epidemiology and nutrition; (b) review and field test appropriate measures for collecting exposure, non-volatile biomarker, and anthropometric data; and (c) build skills in advanced spatial, multi-level and panel regression modeling. I will combine these skills with my existing expertise in the analysis of natural resource management policies and welfare outcomes to become a leading researcher at the intersection of population, environment, and health.